Analysis of Mental Workload and Musculoskeletal Disorders among

IT Workers

Clara Theresia

and Yasmin Nabilla

Department of Industrial Engineering, Faculty of Industrial Technology, Universitas Katolik Parahyangan, Bandung,

Indonesia

Department of Industrial Engineering, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung, Indonesia

Keywords: NASA TLX, Nordic Musculoskeletal Questionnaire, mental demand.

Abstract: Interaction between human and computer for long periods has the potential impact of discomfort and

musculoskeletal disorders. The purpose of this study was to analyze subjective mental workload and its

correlation with musculoskeletal disorders among Information Technology (IT) workers in Bandung,

Indonesia. This research consisted of eighty-seven IT workers, with an average of 25 years (21 to 34 years).

Participants were asked to fill out questionnaires about demographic data, NASA Task Load Index (TLX)

and Nordic Musculoskeletal Questionnaire (NMQ). Generally, IT workers have experienced pain in the

neck (35%), shoulder (29%), and upper back (24%). The result of mental workload assessment using

NASA-TLX concluded that mental demands with 84% rating score and temporal demands with 64%

contributed most of the total NASA-TLX score (69.5% ± 10.24). Pearson correlation result showed a

significant correlation between NASA-TLX score and one of NMQ dimension (lower back) with value r

(87) = 0.216 (p<0.05).

1 INTRODUCTION

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(Smith, 1998).

Human-computer interaction between workers

and computers had the risk of causing physical and

mental discomfort and injury. About 70% of

professional IT workers experienced muscle injuries

due to using a computer in the long-term (Sharan et

al, 2011). Mehta and Parijat's research reported that

about 25% of IT employees suffered muscle

injuries to the neck and back (Mehta.and Parijat,

2012). Injuries and discomfort are also experienced

by bank employees in Iran where a total of 78.5%

complained of musculoskeletal disorders in the neck

and back (Darvishi et al, 2016). In addition,

complaints and injuries are experienced by workers

who usually interact with computers. The results

showed that 73% of workers had complaints in the

back and 71% had complaints in the neck of a total

of 254 respondents using the Musculoskeletal

Symptoms of the Questionnaire (Cho et al, 2012).

Jafari and colleagues have been proved that 56.9%

of Bank employees in Yazd-Iran had

musculoskeletal complaints, especially in the neck

and lower back [6]. Similar findings were found that

bank employees had a musculoskeletal disorder

highly distributed to parts of the body namely 48%

in the neck, 44% in the lower back and 36% in the

upper back (Darvishi et al, 2016). Musculoskeletal

disorder can be assessed using the NORDIC

questionnaire, consisting of 11 rating scales from 0

to 10 where scale 0 means no pain until scale 10

means feels very painful or injured (Kuorinka et al,

1987).

There are two classifications of workload,

namely physical and mental workload. Physical

workload is commonly defined as a workload that

required physical activity and often results in long-

term musculoskeletal disorder. Meanwhile, mental

workload is a load that arises due to work activities

related to cognitive processes such as attention,

planning, logical reasoning, and decision making

(Toomingas et al, 2012). Several approaches can be

used in evaluating and predicting mental workload

include subjective approaches, assessment of

340

Theresia, C. and Nabilla, Y.

Analysis of Mental Workload and Musculoskeletal Disorders among IT Workers.

DOI: 10.5220/0010311200003051

In Proceedings of the International Conference on Culture Heritage, Education, Sustainable Tourism, and Innovation Technologies (CESIT 2020), pages 340-345

ISBN: 978-989-758-501-2

performance and physiological measurements.

Subjective assessment is important in evaluating

workloads because it has practical advantages, easy

implementation and non-intrusiveness. The

interaction between human-machine systems in the

activities of IT companies was very complex so

evaluating employee workloads will become more

difficult. In this case, subjective workload

assessment will greatly useful to assess mental

workload effectively (Toomingas et al, 2012; Rubio

et al, 2004).

Subjective mental workload is an assessment of

mental workload based on the perceptions of each

individual. There are several commonly used

approaches namely Cooper Harper Scale, NASA

Task Load Index (TLX), Subjective Workload

Assessment Technique (SWAT), Rating Scale

Mental Effort (RSME) and Workload Profile [8-9].

NASA-TLX is one of the most widely used multi-

dimensional tools because it was practical with great

validity and reliability.

NASA TLX can be used to measure mental

workload which pioneered by Sandra G. H. and

continues to be developed by Human Performance

Group NASA's Ames Research Center. In the

NASA-TLX, six dimensions are used to measure

workload including mental demand, physical

demand, temporal demand, performance, effort, and

frustration. Each dimensions of NASA-TLX is

assessed by individual perceptions on a scale of 0-

100 (Hart and Staveland, 1988).

NASA-TLX can be used in various research such

as the following studies. Ning et al. tested the

activity of using a touch screen device with NASA-

TLX. Some findings from the experiment that typing

was an activity with the highest mental workload,

followed by reading and playing games

(Ning et al , 2015)The use of NASA-TLX in the

field of aviation has been done to air traffic

controllers, the test results showed that the NASA-

TLX rating is getting higher along with the

increasing number of aircraft (Collet et al, 2009).

Research on emergency medical services also

showed that the hardest task is evacuated casualties

who fall into the mud on steep surfaces with the

condition of patients already very fragile due to the

effects of chemotherapy. In this task, almost all

dimensions had very high ratings except the

performance and frustration dimensions that tend to

be moderate. The smallest mental workload score

from medical personnel’s emergency was on the

activity of testing blood sugar samples (Reuter and

Camba, 2017). NASA-TLX has been used to

examine workers who do physical work such as

lifting, lowering, pushing, and pulling. The worker is

also suffered from pain in the lower back. The

highest rating was mental demand dimensions which

reached 67.12% and followed by effort (62.8%) and

temporal demand (60.8%), while the other

dimensions included a rather high category

(Darvishi et al, 2017) In the nuclear industry, the

user interface layout affected the mental workload of

the operator. Regardless of the good or bad design,

mental demand, temporal demand, and frustration

are contributed significantly to the mental workload

by workers, while the other three dimensions were in

the medium level category (Yan et al, 2017).

Mental workload investigation using NASA-

TLX was used to analyze Bank employee’s

workload in Iran. Major findings from this research

that effort had the highest score (72.8%) and

followed by mental workload (62.7%). Other

findings suggest that subjective mental workload

had a strong correlation with working experience

and marital status (Darvishi et al, 2016). According

to Darvishi et.al, there was a correlation between

mental workload and demographic aspect. There has

been limited research that analyzes about mental

workload and musculoskeletal disorder assessment

using NASA-TLX and Nordic Musculoskeletal

Questionnaire (NMQ) in Indonesia. This study

sought to investigate mental workload and its

correlation to the prevalence of musculoskeletal

disorders among IT workers in Indonesia.

2 METHODS

Eighty-seven respondents (72 male and 15 female)

volunteered to respond to several questionnaires in

this research. The subjects were between the ages of

21 and 34 years (M= 24.8, SD= 2.55). All of the

respondents were IT workers at Bandung, Indonesia.

The subjects must fill a questionnaire about

demographics such as age, education, gender, and

working experience. Subjective mental workload

was assessed using the NASA-TLX (Table 1) (Hart

and Staveland, 1988). Participants also completed

Nordic Musculoskeletal Questionnaire (NMQ)

which is slightly modified by Indonesian

Ergonomics Society in Indonesian version (Fig. 1)

(Perhimpunan Ergonomi Indonesia or Indonesian

Ergonomic Society, 22 July 2019).

Analysis of Mental Workload and Musculoskeletal Disorders among IT Workers

341

Figure 1: Body Sketch used in the Nordic Questionnaire

(Indonesian version).

Table 1: NASA-TLX questionnaire.

Title Scale Descriptions

Mental

Demand

Low/

High

How much mental and

perceptual activity was

required?

(e.g.thinking,

calculating, the task

easy

remembering)

Was

demanding,

simple or complex, exacting or

forgiving?

Physical

Demand

Low/

High

How much physical activity was

required?

(e.g. pushing, pulling, turning,

controlling)

Temporal

Deman

Low/

How much time pressure did

you feel due to

Date or pace at which the

tasks

task elements occurred?

Effort

Low/

High

How hard did you have to work

(

mentall

physically) to accomplish your

erformance?

Performance

Good

Poor

How successful do you think

you were in

accomplishing the goals of the

task set by the experimenter?

Frustration

Low/

High

How insecure, discouraged,

irritated, stressed, and annoyed

versus secure, gratified, content,

relaxed and complacent did you

feel during the task?

3 RESULTS AND DISCUSSIONS

3.1 Demographic Data

Eighty-seven participants were conducted to fill a

questionnaire about demographic data such as age,

gender, working experience, and education

background. Working experience of employees was

1.2 years with the shortest time being 0.5 months

and a maximum of 6.1 years at the time this research

was conducted. In a day, employees worked with an

average of 8.6 ± 1.1 hours excluding 1 hour of free

rest at any time. Mostly, IT workers had

undergraduate education (79.3%) and 18 others had

higher or lower education than undergraduate

(20.7%).

3.2 The Prevalence of Musculoskeletal

Disorders

According to NMQ questionnaire, it was found that

94.25% of respondents had felt pain at least in one

of the nine musculoskeletal body parts. This finding

was in line with Darvishi and colleague’s research

that there was 78.5% of employees who experienced

musculoskeletal complaints during the last 12

months (Darvishi et al, 2016).

Table 2: The prevalence of musculoskeletal disorders of it.

WORKERS

Parts of

Body

Prevalence of

Musculoskeletal

Disorder

(%)

Nec

35.2

Shoulde

29.2

Upper Bac

23.8

Elbow

7.7

Lower Back 23.9

Wris

15.4

Hip/thigh

10.6

Knee

5.5

Ankle

3.2

Table 2 shows the prevalence of musculoskeletal

disorders of IT workers during they worked for the

company. Neck had the highest prevalence of 35.2%

followed by shoulder with 29.2%. The upper back

and lower back also had a high prevalence with

almost the same values of 23.8% and 23.9%

respectively. This was slightly different from Cho

and colleague’s research where the shoulder had the

highest prevalence of 73% followed by 71% neck

and upper back by 60% (Cho et al, 2012). The

characteristics of work mostly sat in front of a laptop

or computer, this was a very common thing if the

CESIT 2020 - International Conference on Culture Heritage, Education, Sustainable Tourism, and Innovation Technologies

342

position or placement of the monitor, keyboard,

mouse, and table was discomfort. Another

possibility that was the condition of the seat was not

in accordance with anthropometry’s size.

Table 3: Correlation test between demographic and

prevalence of musculoskeletal disorders (%).

Correlatio

nTest

Educatio

Gender

Age

Working

Experienc

-0.052 -0.059 0.13 0.082

Shoulde

-0.03 -0.127 0.74 0.211*

Upper

-0.114 -0.036 0.045 -0.027

Elbow

-0.107 -0.007 0.01 0.023

Lower

-0.12 -0.054 0.05 0.054

Wrist 0.232* -0.203 -0.019 0.088

Hip

-0.041 -0.121 -0.019 0.088

Knee -0.005 -0.215* -0.068 0.023

Ankle -0.11 -0.243* -0.025 -0.091

Correlation test using Pearson between

demographic data and the prevalence of

musculoskeletal disorder showed a significant

correlation with p ≤ 0.05 (Table 3). The correlation

between work experience with shoulder pain was r

(87) = 0.211, education level with wrist pain with a

correlation r (87) = 0.232, and gender with pain in

the knee and ankle with a correlation value of r (87)

= -0.215 and r (87) = - 0.243 (Table 4). Others

attribute had a non-significant correlation. This was

in line with Darvishi’s research which concluded

that there was a significant correlation between

subjective workload assessment of marital status and

employee work experience (p <0.001) [4].

3.3 NASA-TLX Score

NASA-TLX rating showed that mental demand was

a greatly factor influencing worker’s workload.

Mostly, employees gave a rating of 84.05 out of 100

on mental demand. The smallest workload was

physical demand with a rating of 21.67. The

physical demand rating was very small because the

employees felt comfortable while sitting at the

computer without doing heavy physical activity.

Other dimensions such as performance, temporal

demand, effort, and frustration have almost the same

range of values, namely between range 59.44 and

69.50. The results of this study suggested that

mental demand had the greatest influence on the

assessment of the mental workload of IT workers.

This was different from the findings obtained by

Darvishi and colleagues where the parameter effort

had the highest weighting value 72.8% (Darvishi et

al, 2016) This could happen because of the different

job characteristics of Bank employees and IT

employees. Weight values are calculated based on

participant answers about which dimensions are the

more influential increasing mental workload. The

overall rating of subjective mental demand can be

calculated by entering the weight into the rating. The

result is concluded that the average employee felt a

subjective mental workload with rating reached 69.5

(SD=10.24). This value showed that the mental

workload of employees on a rather high scale (30-

49) is experienced by 2 people, high (50-79) is

experienced by 68 people and very high ≥80 by 17

people. Table 4 shows complete information about

the assessment of the mental workload using NASA-

TLX.

Table 4: NASA-TLX score.

Statistics

Scale

MD PD P TD E Fr O

Rating

84.

21.67 69.03 66.71 59.44 67.09

11.56 17.9 18.62 15.64 21.65 12.54 10.2

Min

52 2 22 18 12 34 42.7

Max

98 77 99 88 98 97 88.8

Weigh

0.20 0.02 0.21 0.21 0.15 0.20

0.08 0.05 0.08 0.09 0.12 0.08

Min

0.07 0 0 0 0 0

Max

0.33 0.27 0.33 0.33 0.33 0.33

Tall

3.03 0.32 3.10 3.18 2.32 3.03

1.16 0.80 1.26 1.29 1.75 1.20

Min

1 0 0 0 0 0

Max

5 4 5 5 5 5

Analysis of Mental Workload and Musculoskeletal Disorders among IT Workers

343

3.4 Correlation Test between SMWL

and Musculoskeletal Disorders

Correlation test is conducted using Pearson product-

moment to investigate the relationship between

subjective mental workload and prevalence of

musculoskeletal disorders. Table 5 shows that there

was a significant correlation between the Subjective

Mental Workload (SMWL) score and the prevalence

of lower back pain with r(87)= 0.216 (p <0.05).This

result explained that complaints on the lower back

can represent 21.6% of the subjective mental

workload. The eight other body parts did not show a

significant correlation, it was possible because the

working experience of the employees was still

relatively short with an average of 1.2 years.

Table 2: Correlation test between SMWL and prevalence

of musculoskeletal disorder.

Correlation

Test

SMW

Correlation

Test

SMW

Pearson

0.109

Wrist

Pearson

0.015Co

Sig (2

0.315 Sig (2

tailed) 0.889

tailed)

Shoul

Pearson

0.123

Pearson

0.07Co

Sig (2

0.255

Sig (2

tailed

)

0.518tailed

)

Uppe

Bac

Pearson

0.068

Knee

Pearson

-0.038Co

Sig (2

0.534 Sig (2

tailed

)

0.728tailed

)

Elbo

Pearson

0.084

Ankle

Pearson

-0.105

Sig (2

0.44 Sig (2

tailed

)

0.335tailed

)

Lowe

Bac

Pearson

0.216*

Sig (2

tailed

)

0.045

3.5 Ergonomic Design for Office

Workstation

The issue of musculoskeletal disorders and mental

workload among office workers are important to

investigate. Office workstation design should match

with the user-centered requirements or ergonomics

principles to reduce the negative effect of

discomfort, for example, design of space and

furniture need to be associated with specific tasks

and anthropometry’s size (Kroemer and Kroemer,

2017). IT workers had been struggling with some

degree of pain and discomfort especially at neck

(Based on NMQ’s results, neck had the highest

prevalence of disorders with 35.2%). According to

Kroemer and Kroemer (2017), there were several

activities that workers must do to solve this problem.

Firstly, IT workers must avoid sitting over long

periods of time and take 30 minutes of break

(standing, walking and stretching). Secondly,

employees need to change their body position often

to avoid continued compression of tissue, especially

at spinal and muscular fatigue. Finally, workers need

to improve their body movement and posture, for

instance, their trunk, neck, and head erect with only

slight bending, hands-on keyboard and eyes position

on PC/laptop’s screen ((Kroemer and Kroemer,

2017)). Not only workstation components like

computers, furniture, and environment but also other

factor-like job tasks, social activities and the

organizational task should fit IT workers to support

her or his job.

4 CONCLUSIONS

Musculoskeletal disorders and high mental workload

were common problems impact discomfort and

stress among IT workers. This study demonstrated

that almost all IT workers have experienced

complaints at least in one part of the musculoskeletal

body. The greatest prevalence is experienced in the

neck, shoulders, upper back and lower back reached

35%. Complaints in this section are thought to be

due to the characteristics of work that sit more at the

computer and do work that requires high mental

activity so that the body parts are exposed to

unnatural postures. The subjective mental workload

felt by employees is at a rather high to a very high

interval, reached 84% of the score which indicated

the need for re-analysis of the workload received by

employees. The relationship between the value of

the total subjective mental workload and

musculoskeletal disorders can be seen from

CESIT 2020 - International Conference on Culture Heritage, Education, Sustainable Tourism, and Innovation Technologies

344

complaints on the lower back. This research

provides evidence of a link between musculoskeletal

disorder and mental workload. The prevalence of

musculoskeletal disorders at lower back had a

significant correlation with the employee’s mental

workload.

ACKNOWLEDGEMENTS

The author wishes to express their gratitude to

Center for Ergonomic at Department of Industrial

Engineering Universitas Katolik Parahyangan and

Department of Industrial Engineering Institut

Teknologi Bandung.

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